Diagnostic imaging provides a technique for displaying an image of the human body to medical professionals for diagnostic purposes. Diagnostic imaging includes images produced from X-ray, computerized tomography (CT), magnetic resonance imaging (MRI), ultrasound and the like. However, many other medical imaging techniques may be used for diagnostic imaging.
Traditionally, photographic film was generally used for diagnostic imaging. Today, however, diagnostic images are often provided by a digital display device. As an example, digital display devices used in diagnostic imaging may include a cathode ray tube (CRT), Plasma monitors, liquid crystal display (LCD) and the like; however, other display devices may be used.
One concern with using digital display devices for viewing diagnostic images is knowing whether an artifact on the digital display device is from the image being displayed or an artifact in the display device itself. For example, the digital display device may have a particular defect that looks similar to a medical defect for a particular diagnostic image, thus resulting in an incorrect medical diagnosis. Defects in the display devices may be caused by pressure damage, phosphor decay or other types of damage.
In order to prevent a misdiagnosis caused by artifacts in the digital display device, a quality assurance test may be performed on the display device. For instance, a quality assurance test may be performed on the device when the system is first installed or as a periodic quality assurance check. A technique that is currently being used as a quality assurance check is generating a known test pattern on the display and manually scanning the displayed test pattern with a light meter. A sample test pattern is shown in FIG. 1. In particular, FIG. 1 shows a display device 100 displaying a test pattern 110 that includes multiple levels of contrast. A light meter (not shown) is manually held in front of designated locations of the test pattern 110 to measure the alignment of the test pattern and the brightness and contrast of the display device. Contrast refers to the difference in the grayscale of black and white images. For instance, at a particular location, the grayscale value of the reading is compared with the grayscale value of the ideal image. Similarly, for color images, a hue value from the reading of the test image is compared with a hue value of the ideal image. The test results are compared with expected results. From the comparison, defective points in the display device may be detected.
The process of manually holding the light meter in front of the test pattern on the display device is laborious and time consuming. It requires a person to manually hold the light meter in front of the monitor while the test is being conducted and to manually compare the test results with the expected results, therefore, lacking precision and accuracy. Furthermore, manually holding the light meter may result in the light meter being held at multiple angles relative to the surface of the display device, rather than maintaining the light meter consistently parallel with the display device. In addition, this process results in only a portion of the display device being tested. Therefore, the results are not an accurate representation of the entire display device.
Therefore, there is a need for a faster, more accurate and repeatable method of performing a quality assurance test on the display device and automating the process of comparing the test results with the expected results.